AI Medical Compendium Topic

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Mass Screening

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Application of deep learning to predict advanced neoplasia using big clinical data in colorectal cancer screening of asymptomatic adults.

The Korean journal of internal medicine
BACKGROUND/AIMS: We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal neoplasia (ACRN) in asymptomatic adults, based on which colorectal cancer screening could be customized.

An evaluation of DistillerSR's machine learning-based prioritization tool for title/abstract screening - impact on reviewer-relevant outcomes.

BMC medical research methodology
BACKGROUND: Systematic reviews often require substantial resources, partially due to the large number of records identified during searching. Although artificial intelligence may not be ready to fully replace human reviewers, it may accelerate and re...

Artificial Intelligence in Screening Mammography: A Population Survey of Women's Preferences.

Journal of the American College of Radiology : JACR
OBJECTIVE: To investigate the general population's view on the use of artificial intelligence (AI) for the diagnostic interpretation of screening mammograms.

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks.

European radiology
OBJECTIVE: To explore the application of deep learning in patients with primary osteoporosis, and to develop a fully automatic method based on deep convolutional neural network (DCNN) for vertebral body segmentation and bone mineral density (BMD) cal...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

Diabetic medicine : a journal of the British Diabetic Association
AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopathy, while maintaining high specificity for non-referable disease, for clinical implementation within...

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population.

Radiology
Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on ches...

A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity.

PloS one
Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient settin...

[Artificial intelligence for eye care].

Nederlands tijdschrift voor geneeskunde
Technological developments in ophthalmic imaging and artificial intelligence (AI) create new possibilities for diagnostics in eye care. AI has already been applied in ophthalmic diabetes care. AI-systems currently detect diabetic retinopathy in gener...

Machine Learning Strategy for Gut Microbiome-Based Diagnostic Screening of Cardiovascular Disease.

Hypertension (Dallas, Tex. : 1979)
Cardiovascular disease (CVD) is the number one leading cause for human mortality. Besides genetics and environmental factors, in recent years, gut microbiota has emerged as a new factor influencing CVD. Although cause-effect relationships are not cle...